import intake
import ciofs_hindcast_report as chr
import hvplot.pandas # noqa
import ocean_model_skill_assessor as omsa
import pandas as pd
Single CTD profiles across Cook Inlet#
CTD profiles - USGS BOEM
ctd_profiles_usgs_boem
One-off CTD profiles from 2016 to 2021 in July
USGS Cook Inlet fish and bird survey CTD profiles.
CTD profiles collected in Cook Inlet from 2016-2021 by Mayumi Arimitsu as part of BOEM sponsored research on fish and bird distributions in Cook Inlet. The profiles are collected in July for the years 2016-2021.
The scientific project is described here: https://www.usgs.gov/centers/alaska-science-center/science/cook-inlet-seabird-and-forage-fish-study#overview.
cat = intake.open_catalog(chr.CAT_NAME("ctd_profiles_usgs_boem"))
Map of CTD Profiles#
getattr(chr.src.plot_dataset_on_map, "ctd_profiles_usgs_boem")("ctd_profiles_usgs_boem")
2016#
2016102001
cat['2016102001'].plot.data()
2016106001
cat['2016106001'].plot.data()
2016120001
cat['2016120001'].plot.data()
2016122201
cat['2016122201'].plot.data()
2016123001
cat['2016123001'].plot.data()
2016123002
cat['2016123002'].plot.data()
2016125001
cat['2016125001'].plot.data()
2016126001
cat['2016126001'].plot.data()
2016126002
cat['2016126002'].plot.data()
2016205701
cat['2016205701'].plot.data()
2016206001
cat['2016206001'].plot.data()
2016221001
cat['2016221001'].plot.data()
2016223001
cat['2016223001'].plot.data()
2016223002
cat['2016223002'].plot.data()
2016224001
cat['2016224001'].plot.data()
2016225001
cat['2016225001'].plot.data()
2016226001
cat['2016226001'].plot.data()
2017#
2017101001
cat['2017101001'].plot.data()
2017103001
cat['2017103001'].plot.data()
2017120001
cat['2017120001'].plot.data()
2017122001
cat['2017122001'].plot.data()
2017123001
cat['2017123001'].plot.data()
2017124001
cat['2017124001'].plot.data()
2017125001
cat['2017125001'].plot.data()
2017125002
cat['2017125002'].plot.data()
2017201001
cat['2017201001'].plot.data()
2017204001
cat['2017204001'].plot.data()
2017205001
cat['2017205001'].plot.data()
2017206001
cat['2017206001'].plot.data()
2017207001
cat['2017207001'].plot.data()
2017212001
cat['2017212001'].plot.data()
2017214001
cat['2017214001'].plot.data()
2017220001
cat['2017220001'].plot.data()
2017223001
cat['2017223001'].plot.data()
2017224001
cat['2017224001'].plot.data()
2017225001
cat['2017225001'].plot.data()
2018#
2018104001
cat['2018104001'].plot.data()
2018120001
cat['2018120001'].plot.data()
2018121001
cat['2018121001'].plot.data()
2018122001
cat['2018122001'].plot.data()
2018123001
cat['2018123001'].plot.data()
2018124001
cat['2018124001'].plot.data()
2018125001
cat['2018125001'].plot.data()
2018126001
cat['2018126001'].plot.data()
2018203001
cat['2018203001'].plot.data()
2018203002
cat['2018203002'].plot.data()
2018205001
cat['2018205001'].plot.data()
2018208001
cat['2018208001'].plot.data()
2018214002
cat['2018214002'].plot.data()
2018221001
cat['2018221001'].plot.data()
2018223001
cat['2018223001'].plot.data()
2018223002
cat['2018223002'].plot.data()
2018225001
cat['2018225001'].plot.data()
2019#
2019106001
cat['2019106001'].plot.data()
2019121001
cat['2019121001'].plot.data()
2019122001
cat['2019122001'].plot.data()
2019123001
cat['2019123001'].plot.data()
2019125001
cat['2019125001'].plot.data()
2019126001
cat['2019126001'].plot.data()
2019205001
cat['2019205001'].plot.data()
2019210001
cat['2019210001'].plot.data()
2019221001
cat['2019221001'].plot.data()
2019223001
cat['2019223001'].plot.data()
2019223002
cat['2019223002'].plot.data()
2019226001
cat['2019226001'].plot.data()
2021#
2021105001
cat['2021105001'].plot.data()
2021122001
cat['2021122001'].plot.data()
2021123001
cat['2021123001'].plot.data()
2021124001
cat['2021124001'].plot.data()
2021125001
cat['2021125001'].plot.data()
2021126001
cat['2021126001'].plot.data()
2021205001
cat['2021205001'].plot.data()
2021210001
cat['2021210001'].plot.data()
2021221001
cat['2021221001'].plot.data()
2021223001
cat['2021223001'].plot.data()
2021223002
cat['2021223002'].plot.data()
2021224001
cat['2021224001'].plot.data()
2021226001
cat['2021226001'].plot.data()